Comparative resilience of clinical perimetric tests to induced levels of intraocular straylight.

PURPOSE: To investigate the effect of intraocular straylight (IOS) induced by white opacity filters (WOF) on threshold measurements for stimuli employed in three perimeters: standard automated perimetry (SAP), pulsar perimetry (PP) and the Moorfields motion displacement test (MDT).¦METHODS: Four healthy young (24-28 years old) observers were tested six times with each perimeter, each time with one of five different WOFs and once without, inducing various levels of IOS (from 10% to 200%). An increase in IOS was measured with a straylight meter. The change in sensitivity from baseline was normalized, allowing comparison of standardized (z) scores (change divided by the SD of normative values) for each instrument.¦RESULTS: SAP and PP thresholds were significantly affected (P < 0.001) by moderate to large increases in IOS (50%-200%). The drop in motion displacement (MD) from baseline with WOF 5, was approximately 5 dB, in both SAP and PP which represents a clinically significant loss; in contrast the change in MD with MDT was on average 1 minute of arc, which is not likely to indicate a clinically significant loss.¦CONCLUSIONS: The Moorfields MDT is more robust to the effects of additional straylight in comparison with SAP or PP.

Use of flow cytometric methods for single-cell analysis in environmental microbiology

Flow cytometry (FCM) is emerging as an important tool in environmental microbiology. Although flow cytometry applications have to date largely been restricted to certain specialized fields of microbiology, such as the bacterial cell cycle and marine phytoplankton communities, technical advances in instrumentation and methodology are leading to its increased popularity and extending its range of applications. Here we will focus on a number of recent flow cytometry developments important for addressing questions in environmental microbiology. These include (i) the study of microbial physiology under environmentally relevant conditions, (ii) new methods to identify active microbial populations and to isolate previously uncultured microorganisms, and (iii) the development of high-throughput autofluorescence bioreporter assays

The molecular basis of social behavior: models, methods and advances.

Elucidating the molecular and neural basis of complex social behaviors such as communal living, division of labor and warfare requires model organisms that exhibit these multi-faceted behavioral phenotypes. Social insects, such as ants, bees, wasps and termites, are attractive models to address this problem, with rich ecological and ethological foundations. However, their atypical systems of reproduction have hindered application of classical genetic approaches. In this review, we discuss how recent advances in social insect genomics, transcriptomics, and functional manipulations have enhanced our ability to observe and perturb gene expression, physiology and behavior in these species. Such developments begin to provide an integrated view of the molecular and cellular underpinnings of complex social behavior.

Determination of oseltamivir and oseltamivir carboxylate in human plasma by liquid chromatography-tandem mass spectrometry

Introduction: Oseltamivir phosphate (OP), the prodrug of oseltamivir carboxylate (OC; active metabolite), is marketed since 10 years for the treatment of seasonal influenza flu. It has recently received renewed attention because of the threat of avian flu H5N1 in 2006-7 and the 2009-10 A/H1N1 pandemic. However, relatively few studies have been published on OP and OC clinical pharmacokinetics. The disposition of OC and the dosage adaptation of OP in specific populations, such as young children or patients undergoing extrarenal epuration, have also received poor attention. An analytical method was thus developed to assess OP and OC plasma concentrations in patients receiving OP and presenting with comorbidities or requiring intensive care. Methods: A high performance liquid chromatography coupled to tandem mass spectrometry method (HPLC-MS/MS) requiring 100-µL aliquot of plasma for quantification within 6 min of OP and OC was developed. A combination of protein precipitation with acetonitrile, followed by dilution of supernant in suitable buffered solvent was used as an extraction procedure. After reverse phase chromatographic separation, quantification was performed by electro-spray ionization-triple quadrupole mass spectrometry. Deuterated isotopic compounds of OP and OC were used as internal standards. Results: The method is sensitive (lower limit of quantification: 5 ng/mL for OP and OC), accurate (intra-/inter-assay bias for OP and OC: 8.5%/5.5% and 3.7/0.7%, respectively) and precise (intra-/inter-assay CV%: 5.2%/6.5% and 6.3%/9.2%, respectively) over the clinically relevant concentration range (upper limits of quantification 5000 ng/mL). Of importance, OP, as in other previous reports, was found not to be stable ex vivo in plasma on standard anticoagulants (i.e. EDTA, heparin or citrate). This poor stability of OP has been prevented by collecting blood samples on commercial fluoride/oxalate tubes. Conclusions: This new simple, rapid and robust HPLC-MS/MS assay for quantification of OP and OC plasma concentrations offers an efficient tool for concentration monitoring of OC. Its exposure can probably be controlled with sufficient accuracy by thorough dosage adjustment according to patient characteristics (e.g. renal clearance). The usefulness of systematic therapeutic drug monitoring in patients appears therefore questionable. However, pharmacokinetic studies are still needed to extend knowledge to particular subgroups of patients or dosage regimens.

Toward a Statistically Robust Assessment of Social and Solidarity Economy Actors. Conceptual Development and Empirical Validation

Many definitions and debates exist about the core characteristics of social and solidarity economy (SSE) and its actors. Among others, legal forms, profit, geographical scope, and size as criteria for identifying SSE actors often reveal dissents among SSE scholars. Instead of using a dichotomous, either-in-or-out definition of SSE actors, this paper presents an assessment tool that takes into account multiple dimensions to offer a more comprehensive and nuanced view of the field. We first define the core dimensions of the assessment tool by synthesizing the multiple indicators found in the literature. We then empirically test these dimensions and their interrelatedness and seek to identify potential clusters of actors. Finally we discuss the practical implications of our model.

Mapping of Environmental Data Using Kernel-Based Methods

Recently, kernel-based Machine Learning methods have gained great popularity in many data analysis and data mining fields: pattern recognition, biocomputing, speech and vision, engineering, remote sensing etc. The paper describes the use of kernel methods to approach the processing of large datasets from environmental monitoring networks. Several typical problems of the environmental sciences and their solutions provided by kernel-based methods are considered: classification of categorical data (soil type classification), mapping of environmental and pollution continuous information (pollution of soil by radionuclides), mapping with auxiliary information (climatic data from Aral Sea region). The promising developments, such as automatic emergency hot spot detection and monitoring network optimization are discussed as well.

Comparison of Energy Minimization Methods for 3-D Brain Tissue Classification

This paper presents 3-D brain tissue classificationschemes using three recent promising energy minimizationmethods for Markov random fields: graph cuts, loopybelief propagation and tree-reweighted message passing.The classification is performed using the well knownfinite Gaussian mixture Markov Random Field model.Results from the above methods are compared with widelyused iterative conditional modes algorithm. Theevaluation is performed on a dataset containing simulatedT1-weighted MR brain volumes with varying noise andintensity non-uniformities. The comparisons are performedin terms of energies as well as based on ground truthsegmentations, using various quantitative metrics.

Scaled and adjusted restricted tests in multi-sample analysis of moment structures

We extend to score, Wald and difference test statistics the scaled and adjusted corrections to goodness-of-fit test statistics developed in Satorra and Bentler (1988a,b). The theory is framed in the general context of multisample analysis of moment structures, under general conditions on the distribution of observable variables. Computational issues, as well as the relation of the scaled and corrected statistics to the asymptotic robust ones, is discussed. A Monte Carlo study illustrates thecomparative performance in finite samples of corrected score test statistics.

Some hypothesis tests for the covariance matrix when the dimension is large compared to the sample size

This paper analyzes whether standard covariance matrix tests work whendimensionality is large, and in particular larger than sample size. Inthe latter case, the singularity of the sample covariance matrix makeslikelihood ratio tests degenerate, but other tests based on quadraticforms of sample covariance matrix eigenvalues remain well-defined. Westudy the consistency property and limiting distribution of these testsas dimensionality and sample size go to infinity together, with theirratio converging to a finite non-zero limit. We find that the existingtest for sphericity is robust against high dimensionality, but not thetest for equality of the covariance matrix to a given matrix. For thelatter test, we develop a new correction to the existing test statisticthat makes it robust against high dimensionality.

Robust response transformations based on optimal prediction

Nonlinear regression problems can often be reduced to linearity by transforming the response variable (e.g., using the Box-Cox family of transformations). The classic estimates of the parameter defining the transformation as well as of the regression coefficients are based on the maximum likelihood criterion, assuming homoscedastic normal errors for the transformed response. These estimates are nonrobust in the presence of outliers and can be inconsistent when the errors are nonnormal or heteroscedastic. This article proposes new robust estimates that are consistent and asymptotically normal for any unimodal and homoscedastic error distribution. For this purpose, a robust version of conditional expectation is introduced for which the prediction mean squared error is replaced with an M scale. This concept is then used to develop a nonparametric criterion to estimate the transformation parameter as well as the regression coefficients. A finite sample estimate of this criterion based on a robust version of smearing is also proposed. Monte Carlo experiments show that the new estimates compare favorably with respect to the available competitors.

Simultaneous determination of antidementia drugs by HPLC-MS: validation data of the method and plasma level determinations in 300 patients

Aims: A rapid and simple HPLC-MS method was developed for the simultaneousdetermination of antidementia drugs, including donepezil, galantamine, rivastigmineand its major metabolite NAP 226 - 90, and memantine, for TherapeuticDrug Monitoring (TDM). In the elderly population treated with antidementiadrugs, the presence of several comorbidities, drug interactions resulting frompolypharmacy, and variations in drug metabolism and elimination, are possiblefactors leading to the observed high interindividual variability in plasma levels.Although evidence for the benefit of TDM for antidementia drugs still remains tobe demonstrated, an individually adapted dosage through TDM might contributeto minimize the risk of adverse reactions and to increase the probability of efficienttherapeutic response. Methods: A solid-phase extraction procedure with amixed-mode cation exchange sorbent was used to isolate the drugs from 0.5 mL ofplasma. The compounds were analyzed on a reverse-phase column with a gradientelution consisting of an ammonium acetate buffer at pH 9.3 and acetonitrile anddetected by mass spectrometry in the single ion monitoring mode. Isotope-labeledinternal standards were used for quantification where possible. The validatedmethod was used to measure the plasma levels of antidementia drugs in 300patients treated with these drugs. Results: The method was validated accordingto international standards of validation, including the assessment of the trueness(-8 - 11 %), the imprecision (repeatability: 1-5%, intermediate imprecision:2 - 9 %), selectivity and matrix effects variability (less than 6 %). Furthermore,short and long-term stability of the analytes in plasma was ascertained. Themethod proved to be robust in the calibrated ranges of 1 - 300 ng/mL for rivastigmineand memantine and 2 - 300 mg/mL for donepezil, galantamine and NAP226 - 90. We recently published a full description of the method (1). We found ahigh interindividual variability in plasma levels of these drugs in a study populationof 300 patients. The plasma level measurements, with some preliminaryclinical and pharmacogenetic results, will be presented. Conclusion: A simpleLC-MS method was developed for plasma level determination of antidementiadrugs which was successfully used in a clinical study with 300 patients.